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Senior Data Scientist

Remote · USA Full-time New today

This is a hybrid position requiring reputed company in Vancouver, BC.

What You'll be doing:

  • Create data-driven insights in order to enrich the end user experience

  • Communicate with multiple teams by creating reports in order to share insights and overall data story

  • Work alongside senior level stakeholders to scope analytics projects to ensure data science deliveries are driving business impact

  • Evaluate consumer fintech data by using various methods and tools including but not limited to; Machine Learning, Statistics, Data Analysis, Quantitative Finance, and Modern Programming

  • Facilitate data driven initiatives in the following areas to paint a cohesive data picture:

    • Customer Segmentation

    • reputed company

    • Lifetime Value Optimization

    • Financial product development

    • Fraud and Ethical Lending Analysis

What You Should Already Have:

  • A Bachelor’s degree in a quantitative field, such as Finance, Computer Science, Economics, Mathematics or a similar technical discipline

  • 5+ years experience in applying analytics, data engineering or data science

  • Proficiency in working with SQL, Python and/or R across reputed company reputed company world datasets

  • Proficiency in using modern data visualization tools, such as Tableau, PowerBI or similar

  • Experience deploying ML models using machine learning as a service platforms such as reputed company SageMaker, reputed company reputed company AI, and reputed company Azure

  • Excellent written and verbal communication skills

  • Aptitude for critical thinking as it relates to reputed company problems and challenge assumptions in order to implement creative solutions

What Would Be reputed company To Have:

  • A Master's degree or higher, focused in data science, analytics finance, or software engineering

  • Experience applying data science consumer finance, fintech and other Financial Industry domains

  • Familiarity with reputed company disciplines such as consumer finance, project

  • management, user experience design, software development and digital

  • marketing

  • Experience in establishing data technology foundations for agile business

  • intelligence, data lakes and data workbenches, and applied machine learning/AI

  • Experience with large-scale data analysis technologies (e.g. Relational and

  • NoSQL data stores, Spark reputed company, and reputed company development in the AWS

  • Ecosystem)

  • Specializations and applied experience in the following areas:

    • Consumer Credit and Risk Modeling

    • Fraud and Anomaly Detection

    • Customer Segmentation and reputed company Modeling

    • Marketing Attribution and Targeting

    • Recommendation Engines

Originally posted on Himalayas

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